Despite the success of convolutional neural networks (CNNs) in many comp...
Generative adversarial networks are the state of the art approach toward...
The recent successes and wide spread application of compute intensive ma...
In this work, we evaluate two different image clustering objectives, k-m...
Generative convolutional deep neural networks, e.g. popular GAN
architec...
We introduce an open source python framework named PHS - Parallel
Hyperp...
We introduce an open source python framework named PHS - Parallel
Hyperp...
The term attribute transfer refers to the tasks of altering images in su...
Multiple Object Tracking (MOT) is a long-standing task in computer visio...
Most machine learning methods require careful selection of hyper-paramet...
Deep generative models have recently achieved impressive results for man...
Recent studies have shown remarkable success in image-to-image translati...
Current training methods for deep neural networks boil down to very high...
Recent deep learning based approaches have shown remarkable success on o...
In this preliminary report, we present a simple but very effective techn...
Deep learning is finding its way into the embedded world with applicatio...
Recent research implies that training and inference of deep neural netwo...
The idea to use automated algorithms to determine geological facies from...
This paper presents a theoretical analysis and practical evaluation of t...